6 research outputs found
Simulation of spectral bands of the MERIS sensor to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region
Nowadays, the monitoring of water is essential for the sustainability and better management of water resources. The use of remote sensing data is important, since it allows evaluation of dynamic problems in aquatic systems, such as the eutrophication of bodies of water and suspended sediment. The aim of this study was to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region of Brazil using simulated orbital-sensor data, as an aid in the management of water resources. The study area corresponded to the Orós reservoir, in the State of Ceará, Brazil. Water samples for analysis of the chlorophyll-a and measurements of the spectral radiance of the aquatic system were collected from 20 points. The radiance was measured by spectroradiometer. The data were collected in June and August of 2011. The model using three bands of the MERIS sensor (7, 9 and 10) presented an R2 of 0.84. For the two-band model (7 and 9), the value of R2 was 0.85. The waters of the Orós reservoir were all classified as eutrophic. The main optically active component in modelling the shape of the spectra was chlorophyll-a. The models showed a mean absolute error (MAE) of 3.45 and 3.61 μg L-1 for the three- and two-band models respectively. The models displayed high coefficients of determination, i.e. the simulations show the feasibility of estimating chlorophyll-a concentration from the data of the MERIS orbital sensor
Assessment of in vivo fluorescence method for chlorophyll-a estimation in optically complex waters (Curuai floodplain, Par\ue1 - Brazil)
Análise espectral in situ e orbital para a estimativa da concentração de clorofila-a no reservatório da UHE de Funil - RJ
Spectral algorithms can be used to estimate chlorophyll-a concentration in optically complex aquatic ecosystems. The absorption and scattering characteristics of chlorophyll-a in water can be used to construct bio-optics models to estimate its concentration from spectral data obtained by in situ and satellite sensors. The Funil reservoir is known as a eutrophic environment with frequent episodes of algal blooms, which changes the optical characteristics of the water. To evaluate the potential use of spectral algorithms for chlorophyll-a estimation in this reservoir in situ radiometric and limnological measurements were performed, and MERIS sensor data obtained. We tested NIR/Red, NDVI and First Derivative Spectral algorithms. The field spectra and MERIS sensor data showed diagnostic features of chlorophyll-a in green, red and near-infrared regions. The First Derivative highlighted the feature around 690 nm, while most significant adjustments for field spectra were among NDVI and NIR/Red ratio and log-transformed chlorophyll-a values, with R² of 0.78 and 0.77, respectively. For MERIS sensor data adjustments were less significant, with R² of 0.35 for the regression between NDVI and chlorophyll-a, possibly by interference with the signal due to the low resolution image format and narrow reservoir. Nevertheless, as well as the in situ spectra, the main features of chlorophyll-a were identified in the MERIS image.Pages: 5888-589
Simulation of spectral bands of the MERIS sensor to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region
Nowadays, the monitoring of water is essential for the sustainability and better management of water resources. The use of remote sensing data is important, since it allows evaluation of dynamic problems in aquatic systems, such as the eutrophication of bodies of water and suspended sediment. The aim of this study was to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region of Brazil using simulated orbital-sensor data, as an aid in the management of water resources. The study area corresponded to the Orós reservoir, in the State of Ceará, Brazil. Water samples for analysis of the chlorophyll-a and measurements of the spectral radiance of the aquatic system were collected from 20 points. The radiance was measured by spectroradiometer. The data were collected in June and August of 2011. The model using three bands of the MERIS sensor (7, 9 and 10) presented an R2 of 0.84. For the two-band model (7 and 9), the value of R2 was 0.85. The waters of the Orós reservoir were all classified as eutrophic. The main optically active component in modelling the shape of the spectra was chlorophyll-a. The models showed a mean absolute error (MAE) of 3.45 and 3.61 μg L-1 for the three- and two-band models respectively. The models displayed high coefficients of determination, i.e. the simulations show the feasibility of estimating chlorophyll-a concentration from the data of the MERIS orbital sensor
Atualização e correção do delineamento de áreas alagáveis para a bacia Amazônica
Delineation and characterization of areas subject to periodical inundation remains a challenge in the study of Amazonian wetlands, considering the geographical complexity of these environments. Hess et al. (2003) performed the only existing wetland habitat map for the mainstem Amazon floodplain, using synthetic aperture radar images from the Japanese Earth Resources Satellite 1 (JERS-1). These authors have produced a wetlands mask product for the entire basin, which has been used extensively by researchers. Recent studies have shown evidence of geometric distortion and mapping inconsistencies in this product, resulting from the process of automatic delimitation. The present paper analyzes a procedure for revision and correction of the original mask product, identifying the main types of distortion and comparing area differences between original and edited products. The revision procedure was based on visual interpretation and manual digitization of the original mask product, based on three main image sources: the original JERS-1 high water mosaic, the Shuttle Radar Topography Mission global elevation dataset, and a mosaic of orthorectified LandsatTM + images from the GeoCover dataset. The use of two additional sources was invaluable to resolve ambiguities and inconsistencies in areas where JERS-1 images did not allow clear distinction of wetlands. Considering the first 40 1\ub0 x 1\ub0 grid cells edited to date, the results show that the difference in area between the original and corrected masks was of approximately 3500 km² (3% of the total corrected area). Grid cells with the largest variation had a decreasing trend in area, reaching up to 16%. Most grid cells, however, had up to 10% reduction over the originally mapped area, suggesting a slight overestimation of the wetlands by Hess et al. 2003 research.Pages: 5864-587
Simulação de uma imagem WFI/CBERS-3 para a classificação de massas dágua no Reservatório de Ibitinga SP
Even though currently there are a lot of sensors with adequate spectral and radiometric resolutions and field of view to the water properties characterization, the low spatial resolution limits the application of their images on the inland water study. The WFI sensor that will be launched at the CBERS-3 satellite may fill this gap by having spectral, radiometric and spatial characteristics that attend the application needs for inland water studies. To assess a sensor performance before its launch there are available image simulation methods. This article aimed to assess the potential of a WFI/CBERS-3 image to distinguish optically distinct water masses in the Ibitinga ReservoirSP. Therefore, it was accomplished the image simulation of this sensor from a QuickBird scene, which has similar spectral and radiometric properties to the WFI sensor. Unsupervised classifications were performed with different numbers of spectral classes for the simulated image and for a TM/Landsat-5 image (resampled to the same pixel size). It was realized that the application of high radiometric resolution images allows the obtaining of better results for the optically distinct water masses classification. However, the use of high spatial resolution images on the simulation process may complicate the water masses distinction due to the direct surface reflection of the Sun light. The surface water ripples caused by the wind action intensify the brightness in these images, damaging the classification. Nevertheless, the WFI/CBERS-3 image simulation indicated a high potential of this sensor to water quality studies in inland aquatic systems.Pages: 2530-253